Heroic Lifesaver

$GE Vernova(GEV.US)

Post 5 of Episode 23

Context: My original interest in GE Vernova was simple: AI needs enormous amounts of electricity, and power is becoming one of the biggest constraints on data-centre growth. What has strengthened the thesis is that this is now showing up in the numbers. GEV ended Q2 with a $176 billion backlog, while gas-power equipment backlog and slot reservations reached 116 GW. Even more striking, data-centre orders within Electrification exceeded $5 billion in the first half of 2026 — already more than double the total for all of 2025.

My trade: I increasingly see GEV not simply as an AI-adjacent power play, but as a company monetising scarcity across both generation and the grid. Gas turbines address the need for dependable new power, while its electrification businesses help move and transform that electricity. The Prolec GE acquisition adds further exposure to the transformer and grid-equipment side of that bottleneck.

Takeaway: A good thematic investment becomes more interesting when the story starts turning into orders. For GEV, AI’s power problem is no longer just a future forecast — increasingly, it is becoming backlog.

@Captain's Treasure

$SPDR Gold Shares(GLD.US)

Post 4 of Episode 23

Update on GLD.

Context: What I find interesting about gold today is that the macro picture is pulling it in opposite directions. Higher rates and bond yields are clear headwinds, yet inflation remains elevated, geopolitical uncertainty persists and central banks continue to view gold as an increasingly important reserve asset.

My trade: That is why I don’t view GLD simply as a proxy to falling interest rates. I hold it as a macro counterweight — something that can respond to risks that may not be captured by my growth and technology positions. I’m comfortable letting it play that role even when the immediate monetary-policy environment is challenging.

Takeaway: Gold doesn’t need every macro variable to line up perfectly. Sometimes its value is greatest when the economic signals themselves are contradictory. When inflation, rates, geopolitics and asset prices are pulling in different directions, diversification becomes the thesis.

@Captain's Treasure

Apparently all the market needed was… a Muse. 😂

$Meta Platforms(META.US) launches its new personal AI agent, it shoots to the top of the App Store, Meta jumps about 11% in a day… and suddenly the whole market remembers:

“Oh yes. We like AI again.” 😂

Muse has already pulled in around 2.8 million downloads in its first 12 days, and the excitement spilled beyond Meta into the broader AI trade, including names like AMD and Intel.

What I find interesting isn’t just Meta’s move.

It’s what Muse potentially represents.

We’ve spent the last few years talking about AI models getting smarter.

Now we’re moving toward AI that actually does things — books, buys, searches, organises, communicates and works in the background for you. Meta itself describes Muse as an agent designed to take actions across apps rather than simply answer questions.

And if agentic AI really takes off, that means a lot more inference, orchestration, memory, networking and compute happening continuously in the background.

Which probably explains why Mr Market saw one popular AI app and immediately went:

“MORE CHIPS!” 😂

Of course, a few million downloads don’t suddenly justify every AI valuation on earth.

But Muse has done something important.

It has reminded the market that the next phase of AI may not just be about building bigger models.

It may be about getting AI into the hands of ordinary people — and actually giving them a reason to use it every day.

And judging by Monday’s market reaction…

Wall Street appears to have found its Muse too.

Aren’t we all a’muse’d? Sorry I can’t help the pun! The topic was calling for a (pun) chline! 🤓😂

@Captain Leo

$Sandisk(SNDK.US)

Post 3 of Episode 23

An update on Sandisk

Context: What makes SanDisk interesting to me is that NAND is still a cyclical business — but this cycle may be developing differently. Years of disciplined capacity investment, rising data-centre demand and tighter supply can create an environment where storage manufacturers regain pricing power instead of simply competing on volume.

My trade: I see SNDK as exposure to that potential shift in industry economics. If demand continues growing while supply remains constrained, the upside may come not only from selling more NAND, but from selling it at better prices and under increasingly favourable long-term arrangements.

However, I have trimmed down and might trim further my Sndk holdings for technical reasons one being the time cycle we are entering hence time is of more importance than price here and how price behaves into this time cycle is more important. Hence, I am taking gains and practicing caution here with a view to a re-entry.

Takeaway: Sometimes the investment opportunity is not about discovering a new technology. It is about recognising when the economics of an old one are changing. When something essential becomes scarce, pricing power can become the real catalyst. However, excellent fundamentals do not equate to value. And IMHO, technical analysis provides a good window alongside fundamental valuations for this purpose.

@Captain's Treasure

$AEM SGD(AWX.SG)

Post 2 of Episode 23

This is the stock I was talking about in the previous post.

Context: What interests me about AEM is that as semiconductors become more complex and expensive, the cost of allowing a defective chip to progress further into packaging and system assembly rises dramatically. That makes advanced testing, handling and reliability increasingly important — especially in high-performance computing and AI.

My trade: I see AEM as exposure to the test and reliability layer of the semiconductor ecosystem rather than to any particular accelerator, memory or networking architecture. The thesis is simple: regardless of which chip ultimately wins, increasingly sophisticated devices still need to be tested efficiently and accurately before deployment.

Takeaway: The more valuable the chip, the more valuable it becomes to know that it works. In an AI world obsessed with faster compute, the less glamorous business of testing and reliability may become increasingly important — and that is where AEM earns its place in my portfolio.

@Captain's Treasure

A quick reminder to myself!

The market rallies for a few days… and suddenly we’re all geniuses again 😂

Funny how quickly investing psychology changes.

A few red days and I’m questioning every position in my portfolio.

A few green days and suddenly I’m thinking:

“Yes. Exactly as I predicted.” 😂

Of course, nothing has magically changed about my investing ability.

That’s probably one of the things about a strong market.

When everything is going up, it becomes very easy to confuse a rising tide with stock-picking skill.

So whenever my portfolio starts looking particularly clever, I try to remind myself:

The thesis still matters.

Valuation still matters.

Position sizing still matters.

And perhaps most importantly…

The market has a wonderful way of humbling anyone who starts feeling a little too intelligent. 😂

Enjoy the green days.

Just don’t let them go to your head.

I am watching $VanEck Semiconductor ETF(SMH.US)and $iShares Semiconductor ETF(SOXX.US)closely as a proxy to my portfolio. 👀

@Captain Leo

$UMS(558.SG)

Context: What attracted me to UMS is that it sits further upstream in the semiconductor value chain. It is not an accelerator, memory or networking company; instead, it provides the precision manufacturing and engineering capabilities needed by semiconductor-equipment makers as fabs expand capacity and adopt more advanced processes.

My trade: I added UMS as a Singapore-listed way to participate in the broader semiconductor capital-spending cycle. Rather than relying solely on which AI chip architecture wins, the thesis is that increasing chip complexity and continued fab investment should support demand for the equipment ecosystem that enables production.

Takeaway: In a technology boom, there can be value in owning the companies that help build the factories and tools behind the winners. Sometimes the less visible “picks-and-shovels” businesses offer a different way to participate in the same structural trend.

@Captain's Treasure

Fed day. And I’m not sure the rate decision is even the most important part.

The market has already formed a pretty strong expectation about what the Fed will do tonight, so I’m actually more interested in what comes next.

Is this just a one-off move in response to inflation pressures?

Or does the Fed think rates need to stay higher for longer?

That distinction matters much more to me as an investor.

So tonight I’ll mainly be watching three things:

1. Bond yields. 2. The US dollar. 3. And how tech and crypto react after the announcement.

Sometimes the market reaction tells you much more than the headline itself.

If the Fed sounds hawkish but Treasury yields struggle to move higher, or the dollar fails to strengthen, that would definitely get my attention.

On the other hand, if yields break higher and the dollar follows, liquidity-sensitive assets like tech and crypto could have a tougher time.

So for me, tonight isn’t just about:

“What does the Fed do?”

It’s more about:

“How much has the market already priced in — and what does it do once the news is actually out?”

That’s what I’ll be watching. 👀

@Captain Leo

Is the “AI slowdown” narrative really bearish?

I’ve been thinking about the recent comments from Anthropic’s CEO about slowing down AI development.

And I have to say… I’m not completely buying the way the market is interpreting it.

The safety concerns may well be genuine. But I also can’t ignore the incentives.

If you’re already one of the companies at the frontier of AI, slowing things down — or making the regulatory hurdles higher — doesn’t necessarily hurt you. In fact, it could make life much harder for everyone trying to catch up.

That’s also why I found it interesting that Elon Musk $Tesla(TSLA.US)agreed.

Maybe I’m being cynical 😂, but when competitors suddenly agree that everyone should slow down, one of the first questions I ask is:

Who benefits?

For me, the bigger question as an investor is whether anything has actually changed in the AI infrastructure story.

Are hyperscalers cutting capex?

Are accelerator orders being cancelled?

Is demand for networking, memory, storage or power starting to weaken?

If the answer is no, then I’m not sure a few comments about slowing AI development automatically mean the AI investment cycle is slowing too.

For now, I see this more as a narrative shock than a thesis break.

And perhaps there’s another possibility:

Slower model development could actually mean more spending on inference, safety, testing and infrastructure before the next generation gets released.

That’s the part I’m watching.

What do you think? Genuine concern, strategic positioning… or a bit of both? 😂

@Captain Leo